采用 ICA 的公共信道多干扰源信号的自动识别方法

摘要

A new method was presented to solve the problem of automatic recognition of multi-interfering signals in the common channel.Based on the independent component analysis (ICA), the multi-interfering blind signal sepa-ration technology was adopted to separate the interfering signals , which are mixed at the same time.Also the algo-rithm selected the features of each signal and interference in time domain , frequency domain and high-order cumu-lant domain to complete the recognition of the interfering signals .The computer simulation utilizes the automatic rec-ognition method to solve the problem of two types of signals and four interferences mixed in the same channel , and the results show that after five times of iteration the algorithm achieves convergence with a good performance index of 0.21.The results also indicate that when SNR is more than 10 dB, the accurate interference separation rate is a-bove 95%.And when SNR is less than 10 dB, the recognition rate drops greatly while the separation rate is hardly influenced, which proves the correctness and validity of this method .%　　为解决公共信道中多个干扰信号自动识别的问题，提出了采用独立分量分析（ICA）的多干扰源盲信号分离技术．该方法先对混合的干扰信号进行分离，然后对每路信号和干扰在时域、频域和高阶累积域进行特征提取和自动识别．以4种干扰信号和2种通信信号共信道混合为例进行了仿真实验，仿真结果中该方法迭代5次达到收敛，收敛时的性能指数为0．21，说明信号分离效果较好．当信噪比高于10 dB时，正确分离率达到95％以上；当信噪比低于10 dB时，分离率变化不大而识别率大大下降，由此表明了该方法的正确性和有效性．